grid connected inverter

1. Review of Performance Of Tuned PID Controller For
Speed Control Of DC Motor
Akshay Tajne, Pallavi Rangari , Duryodhan Bankar, Suraj patil
Department of Electrical engineering,, J D College Of Engineering & Management, Nagpur
Abstract: The function of speed control in DC motors is
very essential in the achievement of desirable outputs.
DC motors are designed for use in industrial and
commercial applications such as the pump and blowers,
material handling, system and gear drives, and
adjustable speed drives. Both the nonlinear and linear of
DC motor mathematical model is derived and the system
model also represented in the form of continuous state
space equation. Four type of controllers namely
Proportional-Integral-Derivative (PID) controller are
considered for controlling the speed of dc motor by
giving the step input signal. The system is simulated
using MATLAB/SIMULINK software. The system
responses under the four different controllers are also
analysed and discussed in term of their performances.
Keywords: : DC Motor, PID Controller, Existing tuning,
Steady State Error, , Simulink, MATLAB.
1. INTRODUCTION
DC motors are designed for use in industrial and
commercial applications such as the pump and blowers,
material handling, system and gear drives, and adjustable
speed drives. These motors are used to give rotary speed
and position to a various electromechanical system. The
purpose of developing a control system is to enable stable
control since it has parameters tuning difficulties, non-
linear, poor stability and imprecise control. The whole
system is needed to be modeled first by using a state space
equation. It has been found that this system results a non
linear model. From this nonlinear model, the linearization
process has to be done to simplify the model. After the
linearized model has been acquired, the next task to do is to
control the DC motor according to the required
specifications. In this project, the main task is to control the
speed of the DC motor. If the speed is equal to the reference
signal, it can be concluded that the designed controller is
successful in controlling the speed of the system become
stable. There are four types of controllers considered
namely, PID controller. The performance of the controllers
in controlling the speed of DC motor system is evaluated
via computer simulation using MATLAB/SIMULINK
platform.
The development and applications of power electronics in
industry has directly increased the use of Direct Current
(DC) machine, because they have many good
characteristics, high start torque characteristic, high
response performance, easier to be linear control [1].
Nowadays, their uses are not limited to the car application
(electrics vehicle), but also find applications in weak power
using battery system (motor of toy) and for the electric
traction in the multi-machine systems. The speed of DC
motor can be adjusted or controlled easily to a great extend
to provide easy controllability and high performance [2].
There are many techniques used to control DC motor, for
example proportional integral derivation (PID) and Fuzzy
Logic controller (FLC). Today most famous and most
frequently used type of controller in industry is PID
controller, The PID controller can be reduced the rise time
since the proportional controller has effect on this. It can
also eliminate the steady-state error by using the integral
controller and lastly it can increase the stability of the
system by using the derivative control [5
2. LITERATURE REVIEW
On extensive literature survey we can conclude that the PID
controller has become the most widely used controller in
various application domains because of its simple structure
and easy implementation. The emerging features of
automatic tuning have greatly simplified the use of PID
control PID, self-tuning of PID can be extend it for
numerical control systems applications. Also, it can be
concluded that the PID can able to provide automatic tuning
facility due to which it has received a more attention from
the industrial users. The tuning of PID controllers would be
a large research area. A PID controller has the general form
which is:
In (Killingsworth, 2006), where Kp is proportional gain, Ki
is the integral gain, and Kd is the derivative gain. The PID
controller calculation (algorithm) involves three separate
parameters there are the Proportional, the Integral and
Derivative values. The Proportional value determines the
reaction to the current error, the Integral determines the
reaction based on the sum of recent errors and the
Derivative determines the reaction to the rate at which the
error has been changing. The manual tuning of PID
controllers, which require optimization of three parameters,
is a time consuming task (Killingsworth, 2006). The
weighted sum of these three actions is used to adjust the
process via a control element such as the position of a
control valve, the power supply of a heating element or DC
motor speed and position. A PID controller is found in large
number of company in all industries. The controller is come
into different forms. There are many industrial process
implement the PID controller. The reason is because it is
simple structure and well known Ziegler- Nicholas tuning
algorithm have been develop. Other reason is the controlled
process in an industrial almost can be controlled by PID
controlled with the PID control (Nascu. et al, 2006). But,
the conventional PID controller design usually needs to
retune the parameters like proportional gain, integral time
constant and derivative time constant is mutually by the
skill operator. By Nascu et al, (2006) present work there are
Journal of Engineering Sciences Vol 13 Issue 10,2022, ISSN:0377-9254
www.jespublication.com Page 28

2. renewed interest in PID controllers because of two reasons.
The first reason is they extensively used in application in all
industries. Second, despites the existence of some results
modern optimal control methods are not suitable to deal
with fixed structure and fixed controllers. So, there is much
that remains to be done to modernize PID design methods.
Closed loop controller is keeping motor speed at require set
point under varying load conditions to keep at point value
where (Ogata, 2002). For example, the set point is ramping
up or down at the define rate. The system works if an error
of speed is positive. The motor is running too fast so that
the controller output is reduce. If the load is applied the
motor is slow down and produce negative error. The output
then increase by proportional amount to try and restore the
speed.
PID TUNING There is several methods for tuning a PID.
The most useful model shown in Table 2.1, then by the
most effective methods generally involve the development
of some form of process model, then choosing P, I, and D
based on the dynamic model parameters.
Table 2.1: PID tuning methods
From Chien and Jang (2010) state that an auto-tuner is
something capable of computing the parameters of a
regulator connected to a plant automatically and possibly
without any user interaction apart from initiating the
operation.auto-tuning method of PID controller is proposed,
which combines: modelling of the closed-loop system,
modelling of the process, and tuning formulas in terms of
the relative damping of the transient response to set point
changes. The auto tuned Proportional-Integral-Derivative
(PID) Controllers are designed for applications where large
load changes are expected or the need for extreme accuracy
Method Advantages Disadvantages 1 Manual tuning Not
math require, online method Requires experience personnel
2 Ziegler- Nichols Proven method, online method Process
upset, some try and error, very aggressive tuning 3 Cohen-
Coon Good process model Some math offline method. Only
good for first order process Extremum Seeking Proven by
method Some math method, good in various tunes. 11 and
fast response time exists. The PID parameters are tuned
based on the results of step response simulations to produce
a response with minimal settling time and overshoot.
To address the difficulty, much effort has been invested in
developing systematic tuning method (Killingsworth, 2006)
which PID controller is usually used the Ziegler-Nicholas
method. The Ziegler–Nichols rules for tuning PID
controller have been very influential. The rules do,
however, have severe drawbacks, they use insufficient
process information and the design criterion gives closed
loop systems with poor robustness (Cong and Liang, 2009).
The Ziegler and Nichols developed their tuning rules by
simulating a large number of different processes, and
correlating the controller parameters with features of the
step response (Cong and Liang, 2009). So, the process of
this method is to obtain the parameters according Ziegler-
Nicholas tuning rule can find the desired value
3.CONVENTIONAL CONTROLLER
Conventional controllers were used widely in industry due
to their simplicity and ease of implementation, furthermore
it has given reasonable response in numerous applications.
The most famous conventional feedback controller is PID
controller. 2.6.1 PI Controller P-I controller is mainly used
to eliminate the steady state error resulting from P
controller. However, in terms of the speed of the response
and overall stability of the system, it has a negative impact.
This controller is mostly used in areas where speed of the
system is not an issue. Since P-I controller has no ability to
predict the future errors of the system it cannot decrease the
rise time and eliminate the oscillations. If applied, any
amount of I guarantees set point overshoot
Fig 1 shows the block diagram of PI controller.
PD Controller
The aim of using P-D controller is to increase the stability
of the system by improving control since it has an ability to
predict the future error of the system response. In order to
avoid effects of the sudden change in the value of the error
signal, the derivative is taken from the output response of
the system variable instead of the error signal. Therefore, D
mode is designed to be proportional to the change of the
output variable to prevent the sudden changes occurring in
the control output resulting from sudden changes in the
error signal. In addition, D directly amplifies process noise
therefore D-only control is not used
Journal of Engineering Sciences Vol 13 Issue 10,2022, ISSN:0377-9254
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3. Fig 2block Diagram of PD controller.
PID Controller A proportional–integral–derivative
controller (PID controller) is a generic control loop
feedback mechanism (controller) widely used in industrial
control systems a PID is the most commonly used feedback
controller. A PID controller calculates an error value as the
difference between a measured process variable and a
desired setpoint. The controller attempts to minimize the
error by adjusting the process control inputs. In the absence
of knowledge of the underlying process, PID controllers are
the best controllers. However, for best performance, the PID
parameters used in the calculation must be tuned according
to the nature of the system, while the design is generic, the
parameters depend on the specific system. Figure 2.7 shows
the block diagram of PID controller
Fig 3 Block Diagram of PID controller.
PID Controller Theory The PID controller is probably the
most-used feedback control design. PID is an acronym for
Proportional-Integral-Derivative, referring to the three
terms operating on the error signal to produce a control
signal. If u(t) is the control signal sent to the system, y(t) is
the measured output and r(t) is the desired output, and
tracking error:
𝑒(𝑡) = 𝑟(𝑡) − 𝑦(𝑡)
a PID controller has the general form:
(𝑡) = 𝑘𝑝(𝑡) + 𝑘𝑖 ʃ𝑒(𝑡) + 𝑘𝑑 𝑑 𝑑𝑡 𝑒(𝑡)
The desired closed loop dynamics is obtained by adjusting
the three parameters kp , Ki and kd often iteratively by
tuning and without specific knowledge of a plant model [4].
The proportional term Kp (sometimes called gain) makes a
change to the output that is proportional to the current error
value. The proportional response can be adjusted by
multiplying the error by a constant Kp, called the
proportional gain. Larger values typically mean faster
response since the larger the error, the larger the
Proportional term compensation. An excessively large
proportional gain will lead to process instability and
oscillation [2][4]. Integral term Ki the contribution from the
integral term (sometimes called reset) is proportional to
both the magnitude of the error and the duration of the
error. Summing the instantaneous error over time
(integrating the error) gives the accumulated offset that
should have been corrected previously. The accumulated
error is then multiplied by the integral gain and added to the
controller output. The magnitude of the contribution of the
integral term to the overall control action is determined by
the integral gain, . Larger values imply steady state errors
are eliminated more quickly. The trade-off is larger
overshoot: any negative error integrated during transient
response must be integrated away by positive error before
we reach steady state Derivative term Kd the rate of change
of the process error is calculated by determining the slope
of the error over time (i.e., its first derivative with respect to
time) and multiplying this rate of change by the derivative
gain kd. The magnitude of the contribution of the derivative
term (sometimes called rate) to the overall control action is
termed the derivative gain, kd. Larger values decrease
overshoot, but slows down transient response and may lead
to bad performance due to signal noise amplification in the
differentiation of the error [2][4]. PID Tuning a control loop
is the adjustment of its control parameters
(gain/proportional band, integral gain/reset, derivative
gain/rate) to the optimum values for the desired control
response. Good performance (bounded oscillation) is a
basic requirement, but beyond that, different systems have
different behavior, different applications have different
requirements, and some desiderata conflict. Further, some
processes have a degree of non-linearity and so parameters
that work well at full-load conditions don't work when the
process is starting up from noload; this can be corrected by
gain scheduling (using different parameters in different
operating regions). PID controllers often provide acceptable
control even in the absence of tuning, but performance can
generally be improved by careful tuning, and performance
may be unacceptable with poor tuning [4]. PID tuning is a
difficult problem, even though there are only three
parameters and in principle is simple to describe, because it
must satisfy complex criteria within the limitations of PID
control. There are several methods for tuning a PID loop.
The most effective methods generally involve the
development of some form of process model, then choosing
P, I, and D based on the dynamic model parameters. Manual
tuning methods can be relatively inefficient, particularly if
the loops have response timeson the order of minutes or
longer. The choice of method will depend largely on
whether or not the loop can be taken "offline" for tuning,
and the response time of the system. If the system can be
taken offline, the best tuning method often involves
subjecting he system to a step change in input, measuring
the output as a function of time, and using this response to
determine the control parameters [4].
Manual Tuning is if the system must remain online, one
tuning method is to first set Ki and Kd values to zero.
Increase the Kp until the output of the loop oscillates, then
the Kp should be set to approximately half of that value for
a quarter amplitude decay type response. Then increase Ki
Journal of Engineering Sciences Vol 13 Issue 10,2022, ISSN:0377-9254
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4. until any offset is correct in sufficient time for the process.
However, too much Ki will cause problem. Finally, increase
Kd, if required, until the loop is acceptably quick to reach
its reference after a load disturbance. However, too much
Kd will cause excessive response and overshoot. A fast PID
loop tuning usually overshoots slightly to reach the setpoint
more quickly; however, some systems cannot accept
overshoot, in which case an over damped closed-loop
system is required, which will require a Kp setting
significantly less than half that of the Kp setting causing
oscillation. Table 2-1 explain the Effects of increasing a
parameter independently
4. CONCLUSION
On extensive literature survey we can conclude that the PID
controller has become the most widely used controller in
various application domains because of its simple structure
and easy implementation. The emerging features of
automatic tuning have greatly simplified the use of PID
control. Recently, fractional-order PID combined with the
fuzzy logic system , IMC-PID controller design, optimal
PID control, combination of PID-observer structure are
gradually got attention. In the future, PID based control
such as optimal fractional order PID, f PID can be extend it
for numerical control systems applications. Also, it can be
concluded that the PID can able to provide automatic tuning
facility due to which it has received a more attention from
the industrial users. The tuning of PID controllers would be
a large research area.
REFERENCE
[1]A. P. Singh, U. Narayan, And A. Verma, "Speed Control
Of Dc Motor Using Pid Controller Based On Matlab "
2013.
[2]G. A. B. A. A. Sadiq, E. C. Anene, H. B. Mamman, "A
Fuzzy-Based Speed Control Of Dc Motor Using Combined
Armature Voltage And Field Current," 2013.
[3]M. R. K. A. A. K. U. Ghazali, "Speed Control Of Dc
Motor Under Varying Load Using Pid Controller," 2015.
[4]A. Fatah, "Design And Analysis Of Speed Control
Using Hybrid Pid-Fuzzy Controller For Induction Motors,"
2015
. [5]N. I. B. P. Jabo, "Speed Control Of Dc Motor Using Pid
Controller Implementation With Visual Basic," 2008.
[6]J. N. Rai, "Speed Control Of Dc Motor Using Fuzzy
Logic Technique," 2012.
[7]T. Y. R. Krishna, "Speed Control Of Separately Excited
Dc Motor Using Fuzzy Logic Controller," 2015.
[8] C. Copot, C.I. Muresan, R. De Keyser, "Speed and
Position Control of a Dc Motor Using Fractional Order Pi-
Pd Control ", 2013
Journal of Engineering Sciences Vol 13 Issue 10,2022, ISSN:0377-9254
www.jespublication.com Page 31